Artificial Intelligence, E-Assessment, Mathematics Education, Primary School

The rapid advancement of artificial intelligence (AI) has led to significant transformations in educational assessment practices. AI-supported electronic testing (e-assessment) is gaining attention for its potential to enhance automation, adaptivity, and efficiency in both formative and summative evaluation processes. This study combines a comparative analysis of selected online platforms that utilize AI for e-assessment with the outcomes of action research implemented in real-life school settings. In the first phase, we conducted a functional and pedagogical analysis of various AI-based e-testing tools, focusing on their capabilities for automatic question generation, adaptive item sequencing, and real-time feedback. Special attention was given to the field of mathematics education at the primary level, where accurate knowledge verification and differentiation are essential. In the second phase, we carried out action research at the lower secondary level (ISCED 2) of a primary school, investigating the implementation of AI-generated e-tests in regular mathematics instruction. The study examined not only the cognitive and motivational responses of students to AI-driven assessment but also teachers’ reflections on the practical integration of such tools in their instructional routines. The results indicate that AI-enhanced e-testing offers multiple pedagogical benefits, including increased student engagement, personalization of learning, and more efficient data-driven feedback. However, several limitations were identified, such as technological constraints, challenges in interpreting open-ended responses, and the need for teacher mediation in adapting AI outputs to classroom realities. This research contributes to the ongoing discourse on educational technology by providing empirical evidence and critical reflection on the meaningful integration of AI in assessment. It underscores the importance of equipping educators with both digital and pedagogical competencies to ensure responsible and effective use of AI tools in primary and lower secondary education.

The rapid advancement of artificial intelligence (AI) has led to significant transformations in educational assessment practices. AI-supported electronic testing (e-assessment) is gaining attention for its potential to enhance automation, adaptivity, and efficiency in both formative and summative evaluation processes. This study combines a comparative analysis of selected online platforms that utilize AI for e-assessment with the outcomes of action research implemented in real-life school settings. In the first phase, we conducted a functional and pedagogical analysis of various AI-based e-testing tools, focusing on their capabilities for automatic question generation, adaptive item sequencing, and real-time feedback. Special attention was given to the field of mathematics education at the primary level, where accurate knowledge verification and differentiation are essential. In the second phase, we carried out action research at the lower secondary level (ISCED 2) of a primary school, investigating the implementation of AI-generated e-tests in regular mathematics instruction. The study examined not only the cognitive and motivational responses of students to AI-driven assessment but also teachers’ reflections on the practical integration of such tools in their instructional routines. The results indicate that AI-enhanced e-testing offers multiple pedagogical benefits, including increased student engagement, personalization of learning, and more efficient data-driven feedback. However, several limitations were identified, such as technological constraints, challenges in interpreting open-ended responses, and the need for teacher mediation in adapting AI outputs to classroom realities. This research contributes to the ongoing discourse on educational technology by providing empirical evidence and critical reflection on the meaningful integration of AI in assessment. It underscores the importance of equipping educators with both digital and pedagogical competencies to ensure responsible and effective use of AI tools in primary and lower secondary education.